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mit-b0-finetuned-sidewalks

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sayakpaul HF staff commited on
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Training in progress epoch 4

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Files changed (2) hide show
  1. README.md +29 -18
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -14,24 +14,24 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.6505
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- - Validation Loss: 0.6601
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- - Validation Mean Iou: 0.2774
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- - Validation Mean Accuracy: 0.3400
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- - Validation Overall Accuracy: 0.8158
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- - Validation Per Category Iou: [0. 0.67274147 0.83098512 0.46721789 0.48492165 0.28810209
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- nan 0.30676731 0.41116935 0. 0.73679658 0.
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- 0. nan 0. 0.47421792 0. 0.
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- 0.66232704 0. 0.40729478 0.27226345 0. nan
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- 0. 0.22211219 0.00310618 0. 0.81170746 0.73786496
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- 0.88368738 0. 0.07716099 0.12776685 0. ]
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- - Validation Per Category Accuracy: [0. 0.80048159 0.93309497 0.558633 0.56439564 0.38053253
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- nan 0.46424754 0.60183499 0. 0.92479351 0.
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- 0. nan 0. 0.60493457 0. 0.
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- 0.88399244 0. 0.55428873 0.34754253 0. nan
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- 0. 0.25438648 0.00310618 0. 0.90931833 0.91190458
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- 0.94609539 0. 0.08323588 0.15250888 0. ]
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- - Epoch: 3
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  ## Model description
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@@ -107,6 +107,17 @@ The following hyperparameters were used during training:
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  0.88399244 0. 0.55428873 0.34754253 0. nan
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  0. 0.25438648 0.00310618 0. 0.90931833 0.91190458
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  0.94609539 0. 0.08323588 0.15250888 0. ] | 3 |
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.5810
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+ - Validation Loss: 0.6610
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+ - Validation Mean Iou: 0.2893
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+ - Validation Mean Accuracy: 0.3501
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+ - Validation Overall Accuracy: 0.8173
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+ - Validation Per Category Iou: [0. 0.64601276 0.81866457 0.46535767 0.50543168 0.28373075
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+ nan 0.33004533 0.40404147 0. 0.76223358 0.
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+ 0. nan 0. 0.52641725 0. 0.
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+ 0.65767205 0. 0.39175791 0.25442534 0. nan
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+ 0. 0.30521727 0.03951998 0. 0.82740493 0.75297779
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+ 0.88342457 0. 0.20580056 0.19670152 0. ]
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+ - Validation Per Category Accuracy: [0. 0.73558164 0.95660246 0.55532275 0.61966264 0.32151473
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+ nan 0.47707119 0.54010289 0. 0.91394179 0.
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+ 0. nan 0. 0.63758616 0. 0.
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+ 0.88501875 0. 0.56845175 0.29123233 0. nan
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+ 0. 0.38980592 0.03987322 0. 0.92751577 0.84695264
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+ 0.93293488 0. 0.32582376 0.23722217 0. ]
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+ - Epoch: 4
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  ## Model description
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  0.88399244 0. 0.55428873 0.34754253 0. nan
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  0. 0.25438648 0.00310618 0. 0.90931833 0.91190458
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  0.94609539 0. 0.08323588 0.15250888 0. ] | 3 |
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+ | 0.5810 | 0.6610 | 0.2893 | 0.3501 | 0.8173 | [0. 0.64601276 0.81866457 0.46535767 0.50543168 0.28373075
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+ nan 0.33004533 0.40404147 0. 0.76223358 0.
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+ 0. nan 0. 0.52641725 0. 0.
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+ 0.65767205 0. 0.39175791 0.25442534 0. nan
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+ 0. 0.30521727 0.03951998 0. 0.82740493 0.75297779
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+ 0.88342457 0. 0.20580056 0.19670152 0. ] | [0. 0.73558164 0.95660246 0.55532275 0.61966264 0.32151473
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+ nan 0.47707119 0.54010289 0. 0.91394179 0.
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+ 0. nan 0. 0.63758616 0. 0.
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+ 0.88501875 0. 0.56845175 0.29123233 0. nan
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+ 0. 0.38980592 0.03987322 0. 0.92751577 0.84695264
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+ 0.93293488 0. 0.32582376 0.23722217 0. ] | 4 |
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  ### Framework versions
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